bionic (1) r.watershed.1grass.gz

Provided by: grass-doc_7.4.0-1_all bug

NAME

       r.watershed  - Calculates hydrological parameters and RUSLE factors.

KEYWORDS

       raster,  hydrology,  watershed,  accumulation,  drainage, stream network, stream power index, topographic
       index

SYNOPSIS

       r.watershed
       r.watershed --help
       r.watershed   [-s4mab]   elevation=name     [depression=name]      [flow=name]      [disturbed_land=name]
       [blocking=name]     [threshold=integer]     [max_slope_length=float]    [accumulation=name]    [tci=name]
       [spi=name]   [drainage=name]    [basin=name]    [stream=name]    [half_basin=name]    [length_slope=name]
       [slope_steepness=name]    [convergence=integer]   [memory=integer]   [--overwrite]  [--help]  [--verbose]
       [--quiet]  [--ui]

   Flags:
       -s
           SFD (D8) flow (default is MFD)
           SFD: single flow direction, MFD: multiple flow direction

       -4
           Allow only horizontal and vertical flow of water

       -m
           Enable disk swap memory option: Operation is slow
           Only needed if memory requirements exceed available RAM;  see  manual  on  how  to  calculate  memory
           requirements

       -a
           Use positive flow accumulation even for likely underestimates
           See manual for a detailed description of flow accumulation output

       -b
           Beautify flat areas
           Flow direction in flat areas is modified to look prettier

       --overwrite
           Allow output files to overwrite existing files

       --help
           Print usage summary

       --verbose
           Verbose module output

       --quiet
           Quiet module output

       --ui
           Force launching GUI dialog

   Parameters:
       elevation=name [required]
           Name of input elevation raster map

       depression=name
           Name of input depressions raster map
           All non-NULL and non-zero cells are considered as real depressions

       flow=name
           Name of input raster representing amount of overland flow per cell

       disturbed_land=name
           Name of input raster map percent of disturbed land
           For USLE

       blocking=name
           Name of input raster map blocking overland surface flow
           For USLE. All non-NULL and non-zero cells are considered as blocking terrain.

       threshold=integer
           Minimum size of exterior watershed basin

       max_slope_length=float
           Maximum length of surface flow in map units
           For USLE

       accumulation=name
           Name for output accumulation raster map
           Number of cells that drain through each cell

       tci=name
           Name for output topographic index ln(a / tan(b)) map

       spi=name
           Stream power index a * tan(b)
           Name for output raster map

       drainage=name
           Name for output drainage direction raster map
           Directions numbered from 1 to 8

       basin=name
           Name for output basins raster map

       stream=name
           Name for output stream segments raster map

       half_basin=name
           Name for output half basins raster map
           Each half-basin is given a unique value

       length_slope=name
           Name for output slope length raster map
           Slope length and steepness (LS) factor for USLE

       slope_steepness=name
           Name for output slope steepness raster map
           Slope steepness (S) factor for USLE

       convergence=integer
           Convergence factor for MFD (1-10)
           1 = most diverging flow, 10 = most converging flow. Recommended: 5
           Default: 5

       memory=integer
           Maximum memory to be used with -m flag (in MB)
           Default: 300

DESCRIPTION

       r.watershed generates a set of maps indicating: 1) flow accumulation, drainage direction, the location of
       streams and watershed basins, and 2) the LS and S factors of the Revised  Universal  Soil  Loss  Equation
       (RUSLE).

NOTES

       Without flag -m set, the entire analysis is run in memory maintained by the operating system. This can be
       limiting, but is very fast. Setting this flag causes the program to manage memory on  disk  which  allows
       very large maps to be processed but is slower.

       Flag -s force the module to use single flow direction (SFD, D8) instead of multiple flow direction (MFD).
       MFD is enabled by default.

       By -4 flag the user allow only horizontal and vertical flow  of  water.  Stream  and  slope  lengths  are
       approximately  the  same  as outputs from default surface flow (allows horizontal, vertical, and diagonal
       flow of water).  This flag will also make the drainage basins look more homogeneous.

       When -a flag is specified the module will use positive flow accumulation even for likely  underestimates.
       When this flag is not set, cells with a flow accumulation value that is likely to be an underestimate are
       converted to the negative. See below for a detailed description of flow accumulation output.

       Option convergence specifies convergence factor for MFD. Lower values result in higher  divergence,  flow
       is  more widely distributed. Higher values result in higher convergence, flow is less widely distributed,
       becoming more similar to SFD.

       Option elevation specifies the elevation data on which entire analysis is based. NULL (nodata) cells  are
       ignored,  zero  and negative values are valid elevation data.  Gaps in the elevation map that are located
       within the area of interest must be filled beforehand, e.g. with r.fillnulls, to avoid distortions.   The
       elevation map need not be sink-filled because the module uses a least-cost algorithm.

       Option depression specifies the optional map of actual depressions or sinkholes in the landscape that are
       large enough to slow and store surface runoff from a storm event.  All cells that are not  NULL  and  not
       zero indicate depressions. Water will flow into but not out of depressions.

       Raster  flow  map  specifies amount of overland flow per cell.  This map indicates the amount of overland
       flow units that each cell will contribute to the watershed basin model. Overland flow units represent the
       amount of overland flow each cell contributes to surface flow. If omitted, a value of one (1) is assumed.

       Input  Raster  map  or  value containing the percent of disturbed land (i.e., croplands, and construction
       sites) where the raster or input value of 17 equals 17%.  If  no  map  or  value  is  given,  r.watershed
       assumes no disturbed land. This input is used for the RUSLE calculations.

       Option  blocking specifies terrain that will block overland surface flow. Blocking cells and streams stop
       the slope length for the RUSLE.  All cells that are not NULL and not zero indicate blocking terrain.

       Option threshold specifies the minimum size of an exterior watershed basin in cells, if no  flow  map  is
       input, or overland flow units when a flow map is given.  Warning: low threshold values will dramactically
       increase run time and generate difficult to read basin  and  half_basin  results.   This  parameter  also
       controls the level of detail in the stream segments map.

       Value  given  by max_slope_length option indicates the maximum length of overland surface flow in meters.
       If overland flow travels greater than the maximum length, the program  assumes  the  maximum  length  (it
       assumes that landscape characteristics not discernible in the digital elevation model exist that maximize
       the slope length).  This input is used for the RUSLE calculations and is a sensitive parameter.

       Output accumulation map contains the absolute value of the amount of overland flow  that  traverses  each
       cell.  This  value  will be the number of upland cells plus one if no overland flow map is given.  If the
       overland flow map is given, the value will be in overland flow  units.  Negative  numbers  indicate  that
       those  cells  possibly have surface runoff from outside of the current geographic region. Thus, any cells
       with negative values cannot have their surface runoff and sedimentation yields calculated accurately.

       Output tci raster map contains topographic index TCI, computed as ln(α / tan(β))  where  α
       is  the  cumulative  upslope area draining through a point per unit contour length and tan(β) is the
       local slope angle. The TCI reflects the tendency of water to accumulate at any point in the catchment and
       the  tendency for gravitational forces to move that water downslope (Quinn et al. 1991).  This value will
       be negative if &#945; / tan(&#946;) < 1.

       Output spi raster map contains stream power index SPI, computed as &#945; * tan(&#946;) where  &#945;  is
       the cumulative upslope area draining through a point per unit contour length and tan(&#946;) is the local
       slope angle. The SPI reflects the power of water flow at any point in the catchment and the tendency  for
       gravitational  forces  to  move that water downslope (Moore et al. 1991).  This value will be negative if
       &#945; < 0, i.e. for cells with possible surface runoff from outside of the current geographic region.

       Output drainage raster map contains drainage direction.  Provides the "aspect" for each cell measured CCW
       from  East.  Multiplying positive values by 45 will give the direction in degrees that the surface runoff
       will travel from that cell.  The value 0 (zero) indicates that the cell is a depression area (defined  by
       the depression input map).  Negative values indicate that surface runoff is leaving the boundaries of the
       current geographic region.  The absolute value of these negative cells indicates the direction  of  flow.
       For MFD, drainage indicates the direction of maximum flow.

       The  output  basin  map contains unique label for each watershed basin. Each basin will be given a unique
       positive even integer.  Areas along edges may not be large enough to create an exterior watershed  basin.
       NULL  values  indicate  that the cell is not part of a complete watershed basin in the current geographic
       region.

       The output stream contains stream segments. Values correspond to the  watershed  basin  values.   Can  be
       vectorized after thinning (r.thin) with r.to.vect.

       The  output  half_basin  raster  map stores each half-basin is given a unique value. Watershed basins are
       divided into left and right sides. The right-hand side cell of the watershed basin (looking upstream) are
       given  even values corresponding to the values in basin.  The left-hand side cells of the watershed basin
       are given odd values which are one less than the value of the watershed basin.

       The output length_slope raster map stores  slope  length  and  steepness  (LS)  factor  for  the  Revised
       Universal  Soil  Loss  Equation  (RUSLE).   Equations taken from Revised Universal Soil Loss Equation for
       Western Rangelands (Weltz et al. 1987). Since the LS factor is a small number (usually  less  than  one),
       the GRASS output map is of type DCELL.

       The  output  slope_steepness  raster  map  stores  slope steepness (S) factor for the Universal Soil Loss
       Equation (RUSLE).  Equations taken from article entitled Revised Slope Steepness Factor for the Universal
       Soil  Loss  Equation (McCool et al. 1987).  Since the S factor is a small number (usually less than one),
       the GRASS output map is of type DCELL.

   AT least-cost search algorithm
       r.watershed uses an AT least-cost search algorithm (see REFERENCES  section)  designed  to  minimize  the
       impact  of  DEM  data  errors.  Compared to r.terraflow, this algorithm provides more accurate results in
       areas of low slope as well as DEMs constructed with techniques that mistake canopy  tops  as  the  ground
       elevation.  Kinner  et  al.  (2005), for example, used SRTM and IFSAR DEMs to compare r.watershed against
       r.terraflow results in Panama. r.terraflow was unable to replicate stream locations in the larger valleys
       while  r.watershed  performed  much  better.  Thus,  if forest canopy exists in valleys, SRTM, IFSAR, and
       similar data products will cause major errors in r.terraflow stream  output.  Under  similar  conditions,
       r.watershed  will generate better stream and half_basin results. If watershed divides contain flat to low
       slope, r.watershed will generate better basin results than r.terraflow. (r.terraflow uses the  same  type
       of  algorithm as ESRI’s ArcGIS watershed software which fails under these conditions.) Also, if watershed
       divides contain forest canopy mixed with uncanopied areas using SRTM, IFSAR, and similar  data  products,
       r.watershed  will  generate better basin results than r.terraflow. The algorithm produces results similar
       to those obtained when running r.cost and r.drain on every cell on the raster map.

   Multiple flow direction (MFD)
       r.watershed offers two methods to calculate surface flow: single flow direction (SFD,  D8)  and  multiple
       flow direction (MFD). With MFD, water flow is distributed to all neighbouring cells with lower elevation,
       using slope towards neighbouring cells as  a  weighing  factor  for  proportional  distribution.  The  AT
       least-cost path is always included. As a result, depressions and obstacles are traversed with a gracefull
       flow convergence before the overflow. The convergence factor causes flow accumulation  to  converge  more
       strongly  with  higher  values.  The supported range is 1 to 10, recommended is a convergence factor of 5
       (Holmgren, 1994). If many small sliver basins are created with MFD, setting the convergence factor  to  a
       higher value can reduce the amount of small sliver basins.

   In-memory mode and disk swap mode
       There  are two versions of this program: ram and seg.  ram is used by default, seg can be used by setting
       the -m flag.

       The ram version requires a maximum of 31 MB of RAM for 1 million  cells.  Together  with  the  amount  of
       system  memory  (RAM)  available,  this  value  can be used to estimate whether the current region can be
       processed with the ram version.

       The ram version uses virtual memory managed by the operating system to store all the data structures  and
       is faster than the seg version; seg uses the GRASS segmentation library which manages data in disk files.
       seg uses only as much system memory (RAM) as specified with the memory option, allowing  other  processes
       to operate on the same system, even when the current geographic region is huge.

       Due to memory requirements of both programs, it is quite easy to run out of memory when working with huge
       map regions. If the ram version runs out of memory and the resolution  size  of  the  current  geographic
       region  cannot be increased, either more memory needs to be added to the computer, or the swap space size
       needs to be increased. If seg runs out of memory, additional disk space needs to  be  freed  up  for  the
       program  to  run.   The r.terraflow module was specifically designed with huge regions in mind and may be
       useful here as an alternative, although disk space requirements of r.terraflow are several  times  higher
       than of seg.

   Large regions with many cells
       The  upper  limit  of  the  ram version is 2 billion (231 - 1) cells, whereas the upper limit for the seg
       version is 9 billion-billion (263 - 1 = 9.223372e+18) cells.
       In some situations, the region size (number of cells) may be too large for the amount of time  or  memory
       available.  Running  r.watershed  may  then require use of a coarser resolution. To make the results more
       closely resemble the finer terrain data, create a map layer containing the lowest elevation values at the
       coarser  resolution. This is done by: 1) Setting the current geographic region equal to the elevation map
       layer with g.region, and 2) Use the r.neighbors or r.resamp.stats command to find the lowest value for an
       area  equal in size to the desired resolution. For example, if the resolution of the elevation data is 30
       meters and the resolution of the geographic region for r.watershed will be 90  meters:  use  the  minimum
       function  for  a  3 by 3 neighborhood. After changing to the resolution at which r.watershed will be run,
       r.watershed should be run using the values from the neighborhood output map  layer  that  represents  the
       minimum elevation within the region of the coarser cell.

   Basin threshold
       The  minimum  size  of  drainage  basins,  defined by the threshold parameter, is only relevant for those
       watersheds with a single stream having  at  least  the  threshold  of  cells  flowing  into  it.   (These
       watersheds  are called exterior basins.)  Interior drainage basins contain stream segments below multiple
       tributaries.  Interior drainage basins can be of any size  because  the  length  of  an  interior  stream
       segment is determined by the distance between the tributaries flowing into it.

   MASK and no data
       The  r.watershed  program  does  not  require  the user to have the current geographic region filled with
       elevation values.  Areas without elevation data (masked or NULL cells) are ignored. It is  NOT  necessary
       to  create  a raster map (or raster reclassification) named MASK for NULL cells.  Areas without elevation
       data will be treated as if they are off the edge of  the  region.  Such  areas  will  reduce  the  memory
       necessary  to run the program.  Masking out unimportant areas can significantly reduce processing time if
       the watersheds of interest occupy a small percentage of the overall area.

       Gaps (NULL cells) in the elevation map that  are  located  within  the  area  of  interest  will  heavily
       influence  the  analysis:  water  will  flow  into  but  not out of these gaps. These gaps must be filled
       beforehand, e.g. with r.fillnulls.

       Zero (0) and negative values will be treated as elevation data (not no_data).

   Further processing of output layers
       Problem areas, i.e. those parts of a basin with a likely  underestimate  of  flow  accumulation,  can  be
       easily identified with e.g.
         r.mapcalc "problems = if(flow_acc < 0, basin, null())"
       If  the region of interest contains such problem areas, and this is not desired, the computational region
       must be expanded until the catchment area for the region of interest is completely included.

       To isolate an individual river network using the output of this module, a number  of  approaches  may  be
       considered.

       1      Use a resample of the basins catchment raster map as a MASK.
              The equivalent vector map method is similar using v.select or v.overlay.

       2      Use the r.cost module with a point in the river as a starting point.

       3      Use the v.net.iso module with a node in the river as a starting point.

       All  individual  river  networks  in  the stream segments output can be identified through their ultimate
       outlet points. These points are all cells in the stream segments output with negative drainage direction.
       These points can be used as start points for r.water.outlet or v.net.iso.

       To  create  river  mile  segmentation  from  a vectorized streams map, try the v.net.iso or v.lrs.segment
       modules.

       The stream segments output can be easily vectorized after thinning with r.thin. Each  stream  segment  in
       the vector map will have the value of the associated basin. To isolate subbasins and streams for a larger
       basin, a MASK for the larger basin can be created with r.water.outlet. The stream segments output  serves
       as  a  guide  where  to place the outlet point used as input to r.water.outlet.  The basin threshold must
       have been sufficiently small to isolate a stream network and subbasins within the larger basin.

       Given that the drainage is  8  directions  numbered  counter-clockwise  starting  from  1  in  north-east
       direction,  multiplying  the  output by 45 (by 45. to get a double precision floating point raster map in
       r.mapcalc) gives the directions in degrees. For  most  applications,  zeros  which  indicate  depressions
       specified  by  depression and negative values which indicate runoff leaving the region should be replaced
       by NULL (null() in r.mapcalc).  The following command performs these replacements:
       r.mapcalc "drainage_degrees = if(drainage > 0, 45. * drainage, null())"
       Alternatively, the user can use the -a flag or later the abs() function in r.mapcalc  if  the  runoff  is
       leaving the region.

EXAMPLES

       These examples use the Spearfish sample dataset.

   Convert r.watershed streams map output to a vector map
       If you want a detailed stream network, set the threshold option small to create lots of catchment basins,
       as only one stream is presented per catchment. The r.to.vect -v flag preserves the catchment  ID  as  the
       vector category number.
         r.watershed elev=elevation.dem stream=rwater.stream
         r.to.vect -v in=rwater.stream out=rwater_stream

       Set a different color table for the accumulation map:
         MAP=rwater.accum
         r.watershed elev=elevation.dem accum=$MAP
         eval `r.univar -g "$MAP"`
         stddev_x_2=`echo $stddev | awk ’{print $1 * 2}’`
         stddev_div_2=`echo $stddev | awk ’{print $1 / 2}’`
         r.colors $MAP col=rules << EOF
           0% red
           -$stddev_x_2 red
           -$stddev yellow
           -$stddev_div_2 cyan
           -$mean_of_abs blue
           0 white
           $mean_of_abs blue
           $stddev_div_2 cyan
           $stddev yellow
           $stddev_x_2 red
           100% red
         EOF

       Create  a  more detailed stream map using the accumulation map and convert it to a vector output map. The
       accumulation cut-off, and therefore fractal dimension, is arbitrary; in this example  we  use  the  map’s
       mean  number  of  upstream  catchment  cells (calculated in the above example by r.univar) as the cut-off
       value. This only works with SFD, not with MFD.
         r.watershed elev=elevation.dem accum=rwater.accum
         r.mapcalc ’MASK = if(!isnull(elevation.dem))’
         r.mapcalc "rwater.course = \
          if( abs(rwater.accum) > $mean_of_abs, \
              abs(rwater.accum), \
              null() )"
         r.colors -g rwater.course col=bcyr
         g.remove -f type=raster name=MASK
         # Thinning is required before converting raster lines to vector
         r.thin in=rwater.course out=rwater.course.Thin
         r.colors -gn rwater.course.Thin color=grey
         r.to.vect in=rwater.course.Thin out=rwater_course type=line
         v.db.dropcolumn map=rwater_course column=label

   Create watershed basins map and convert to a vector polygon map
         r.watershed elev=elevation.dem basin=rwater.basin thresh=15000
         r.to.vect -s in=rwater.basin out=rwater_basins type=area
         v.db.dropcolumn map=rwater_basins column=label
         v.db.renamecolumn map=rwater_basins column=value,catchment

       Display output in a nice way
         r.relief map=elevation.dem
         d.shade shade=elevation.dem.shade color=rwater.basin bright=40
         d.vect rwater_course color=orange

REFERENCES

           •   Ehlschlaeger C. (1989). Using the AT Search Algorithm to Develop Hydrologic Models  from  Digital
               Elevation Data, Proceedings of International Geographic Information Systems (IGIS) Symposium ’89,
               pp 275-281 (Baltimore, MD, 18-19 March 1989).
               URL: http://chuck.ehlschlaeger.info/older/IGIS/paper.html

           •   Holmgren P. (1994). Multiple flow  direction  algorithms  for  runoff  modelling  in  grid  based
               elevation models: An empirical evaluation.  Hydrological Processes Vol 8(4), 327-334.
               DOI: 10.1002/hyp.3360080405

           •   Kinner  D.,  Mitasova  H.,  Harmon  R.,  Toma  L.,  Stallard R. (2005).  GIS-based Stream Network
               Analysis for The Chagres River Basin, Republic of Panama. The Rio  Chagres:  A  Multidisciplinary
               Profile of a Tropical Watershed, R. Harmon (Ed.), Springer/Kluwer, p.83-95.
               URL: http://www4.ncsu.edu/~hmitaso/measwork/panama/panama.html

           •   McCool  et  al.  (1987).  Revised  Slope  Steepness  Factor for the Universal Soil Loss Equation,
               Transactions of the ASAE Vol 30(5).

           •   Metz M., Mitasova H., Harmon R. (2011). Efficient extraction of drainage networks  from  massive,
               radar-based  elevation  models  with  least  cost  path  search, Hydrol. Earth Syst. Sci. Vol 15,
               667-678.
               DOI: 10.5194/hess-15-667-2011

           •   Moore I.D., Grayson R.B., Ladson A.R. (1991). Digital terrain modelling: a review of  hydrogical,
               geomorphological, and biological applications, Hydrological Processes, Vol 5(1), 3-30
               DOI: 10.1002/hyp.3360050103

           •   Quinn  P., K. Beven K., Chevallier P., Planchon O. (1991). The prediction of hillslope flow paths
               for distributed hydrological modelling using Digital Elevation Models, Hydrological Processes Vol
               5(1), p.59-79.
               DOI: 10.1002/hyp.3360050106

           •   Weltz M. A., Renard K.G., Simanton J. R. (1987). Revised Universal Soil Loss Equation for Western
               Rangelands, U.S.A./Mexico Symposium of Strategies for Classification  and  Management  of  Native
               Vegetation for Food Production In Arid Zones (Tucson, AZ, 12-16 Oct. 1987).

SEE ALSO

         g.region,  r.cost,  r.drain,  r.fillnulls, r.flow, r.mask, r.neighbors, r.param.scale, r.resamp.interp,
       r.terraflow, r.topidx, r.water.outlet, r.stream.extract

AUTHORS

       Original version: Charles Ehlschlaeger, U.S. Army Construction Engineering Research Laboratory
       Faster sorting algorithm and MFD support: Markus Metz <markus.metz.giswork at gmail.com>

       Last changed: $Date: 2017-11-24 02:38:11 +0100 (Fri, 24 Nov 2017) $

SOURCE CODE

       Available at: r.watershed source code (history)

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       © 2003-2018 GRASS Development Team, GRASS GIS 7.4.0 Reference Manual